This release adds 2 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Topics
+12 more
Affected surfaces
ReleasePort's take
Moderate signalThe release fixes preview recreation in railway links and splits PydanticAI agent spans at the latest user turn. It also removes console logs that leaked tokens, sessions, and PII from the frontend.
Why it matters: Critical security fix: removal of console logs leaking sensitive data (severity 90).
Summary
AI summaryFixes preview project recreation in railway, splits PydanticAI agent spans in api, and removes token‑leaking console logs from frontend.
Changes in this release
| Type | Severity | Summary | CVE |
|---|---|---|---|
| Security | Critical |
Remove console logs that leak tokens, sessions, and PII. Remove console logs that leak tokens, sessions, and PII. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Feature | Low |
Adds safeguards to the table's click handlers. Adds safeguards to the table's click handlers. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Feature | Low |
Unify eval loops across the system. Unify eval loops across the system. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Re-create preview project when a stale railway link fails. Re-create preview project when a stale railway link fails. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Split PydanticAI agent span messages at the latest user turn. Split PydanticAI agent span messages at the latest user turn. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Render numeric/discrete evaluator metrics as values, not raw stats. Render numeric/discrete evaluator metrics as values, not raw stats. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Render LangChain tool calls in the observability drawer. Render LangChain tool calls in the observability drawer. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Fix playground draft status render for variables. Fix playground draft status render for variables. Source: llm_adapter@2026-06-10 Confidence: high |
— |
| Bugfix | Medium |
Render playground evaluation workbench changelog entry in docs. Render playground evaluation workbench changelog entry in docs. Source: llm_adapter@2026-06-10 Confidence: low |
— |
| Refactor | Low |
Move tracing away from legacy endpoints. Move tracing away from legacy endpoints. Source: llm_adapter@2026-06-10 Confidence: high |
— |
Full changelog
What's Changed
- [release] v0.102.0 by @github-actions[bot] in https://github.com/Agenta-AI/agenta/pull/4547
- [feat] Unify eval loops by @junaway in https://github.com/Agenta-AI/agenta/pull/4341
- fix(railway): re-create preview project when a stale link fails by @mmabrouk in https://github.com/Agenta-AI/agenta/pull/4589
- fix(api): split PydanticAI agent span messages at the latest user turn by @mmabrouk in https://github.com/Agenta-AI/agenta/pull/4588
- [fix] Render numeric/discrete evaluator metrics as values, not raw stats by @mmabrouk in https://github.com/Agenta-AI/agenta/pull/4586
- fix(frontend): remove console logs that leak tokens, sessions, and PII by @ashrafchowdury in https://github.com/Agenta-AI/agenta/pull/4583
- [fix] Render LangChain tool calls in the observability drawer by @mmabrouk in https://github.com/Agenta-AI/agenta/pull/4582
- [FE / chore] Move tracing away from legacy endpoints by @ardaerzin in https://github.com/Agenta-AI/agenta/pull/4573
- [Fix]: playground draft status render for variables by @ashrafchowdury in https://github.com/Agenta-AI/agenta/pull/4585
- docs(docs): add Playground evaluation workbench changelog entry by @mmabrouk in https://github.com/Agenta-AI/agenta/pull/4596
- Fix: Adds safeguards to the table's click handlers by @ashrafchowdury in https://github.com/Agenta-AI/agenta/pull/4540
Full Changelog: https://github.com/Agenta-AI/agenta/compare/v0.102.0...v0.103.0
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LLMOps platform for prompt management, LLM evaluation, and observability. Build, evaluate, and monitor production-grade LLM applications with collaborative prompt engineering.
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